Question · asked by 1 review

High‐intensity vs low‐intensity exercise programmes: Functional ability

It is very uncertain whether high‐intensity changes functional ability (short‐term) FIQ modified (0 to 16; higher scores… compared with low‐intensity exercise programmes (very low certainty).

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
High‐intensity vs low‐intensity exercise programmes
Functional ability (short‐term) FIQ modified (0 to 16; higher scores mean better function) · patients with patellofemoral pain syndrome (untreated PFPS of over 2 months in duration)
It is very uncertain whether high‐intensity changes functional ability (short‐term) FIQ modified (0 to 16; higher scores… compared with low‐intensity exercise programmes (very low certainty).
Exercise for treating patellofemoral pain syndrome (2015) · Cochrane Headline outcomes only
MD 3.7 [1.59, 5.81]1 study · 40 participantsVery low
High‐intensity vs low‐intensity exercise programmes
Functional ability (long‐term) FIQ modified (0 to 16; higher scores mean better function) · patients with patellofemoral pain syndrome (untreated PFPS of over 2 months in duration)
It is very uncertain whether high‐intensity changes functional ability (long‐term) FIQ modified (0 to 16; higher scores… compared with low‐intensity exercise programmes (very low certainty).
Exercise for treating patellofemoral pain syndrome (2015) · Cochrane Headline outcomes only
MD 3.9 [1.72, 6.08]1 study · 28 participantsVery low

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Exercise for treating patellofemoral pain syndrome
2015 · Cochrane Headline outcomes only
Not reportedlist not extracted yetNot assessed

Studies behind the findings

None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.